Model Predictive Control in Industry: Challenges and Opportunities

被引：196
|
作者：
Forbes, Michael G. [1 ]
Patwardhan, Rohit S. [2 ]
Hamadah, Hamza [2 ]
Gopaluni, R. Bhushan [3 ]
机构：
[1] Honeywell Proc Solut, N Vancouver, BC V7J 3S4, Canada
[2] Saudi Aramco, Proc & Control Syst Dept, Dhahran 31311, Saudi Arabia
[3] Univ British Columbia, Dept Chem & Biol Engn, Vancouver, BC V6T 1Z3, Canada
来源：
IFAC PAPERSONLINE | 2015年 / 48卷 / 08期
关键词：
industrial control; process control; model-based control; predictive control; adaptive control; performance monitoring; control applications; human factors; MPC;
D O I：
10.1016/j.ifacol.2015.09.022
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With decades of successful application of model predictive control (MPC) to industrial processes, practitioners are now focused on ease of commissioning, monitoring, and automation of maintenance. Many industries do not necessarily need better algorithms, but rather improved usability of existing technologies to allow a limited workforce of varying expertise to easily commission, use, and maintain these valued applications. Continuous performance monitoring, and automated model re identification are being used as vendors work to deliver automated adaptive MPC. This paper examines industrial practice and emerging research trends towards providing sustained MPC performance. (C) 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：531 / 538
页数：8
相关论文
共 50 条
  • [1] Nonlinear model predictive control: Challenges and opportunities
    Mayne, D
    NONLINEAR MODEL PREDICTIVE CONTROL, 2000, 26 : 23 - 44
  • [2] Opportunities and Challenges of Model Predictive Control in Food Technologies
    Kurtanjek, Zelimir
    PROCEEDINGS OF THE 2008 JOINT CENTRAL EUROPEAN CONGRESS, VOL 1, 2008, : 105 - 110
  • [3] Model Predictive Control for Aircraft Load Alleviation: Opportunities and Challenges
    Kopf, Michael
    Bullinger, Eric
    Giesseler, Hans-Gerd
    Adden, Stephan
    Findeisen, Rolf
    2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC), 2018, : 2417 - 2424
  • [4] Robust model predictive control: reflections and opportunities
    Goodwin, Graham C.
    Kong, He
    Mirzaeva, Galina
    Seron, María M.
    Journal of Control and Decision, 2014, 1 (02) : 115 - 148
  • [5] The Challenges of Predictive Control to reach acceptance in the Power Electronics Industry
    Norambuena, Margarita
    Garcia, Cristian
    Rodriguez, Jose
    2016 7TH POWER ELECTRONICS AND DRIVE SYSTEMS & TECHNOLOGIES CONFERENCE (PEDSTC), 2016, : 636 - 640
  • [6] Model predictive control-status and challenges
    Xi, Yu-Geng
    Li, De-Wei
    Lin, Shu
    Zidonghua Xuebao/Acta Automatica Sinica, 2013, 39 (03): : 222 - 236
  • [7] Distributed predictive control for wind farms efficiency maximization: challenges and opportunities
    Caruntu, Constantin F.
    2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019), 2019, : 452 - 457
  • [8] Cold Atmospheric Plasma Medicine: Applications, Challenges, and Opportunities for Predictive Control
    Kazemi, Ali
    Nicol, McKayla J.
    Bilen, Sven G.
    Kirimanjeswara, Girish S.
    Knecht, Sean D.
    PLASMA, 2024, 7 (01) : 233 - 257
  • [9] Challenges and Opportunities for Petrochemical Industry
    John Zheng
    ChinaChemicalReporter, 2009, 20 (11) : 24 - 24
  • [10] Challenges and opportunities in the semiconductor industry
    Polcari, MR
    2004 INTERNATIONAL CONFERENCE ON INTEGRATED CIRCUIT DESIGN AND TECHNOLOGY, 2004, : 1 - 2
12345